Osteoarthritis (“OA”) of the knee presents a current and growing challenge to the available orthopaedic resources in the United States. At the present time, OA is one of the leading causes of chronic disability, with recent estimates reporting that symptomatic knee OA occurs in 13% of people age 60 years and older (Bauer et al., “Classification of Osteoarthritis Biomarkers: A Proposed Approach,” Osteoarthritis Cartilage 14(8):723-7 (2006); Lawrence et al., “Estimates of the Prevalence of Arthritis and Selected Musculoskeletal Disorders In the United States,” Arthritis Rheum. 41(5):778-99 (1998)). Between 2000 and 2010, the number of total knee replacements (“TKR”) in the U.S. doubled, and is anticipated to approach 3.8 million cases per year by 2030 (Kurtz et al., “Projections of Primary and Revision Hip and Knee Arthroplasty In the United States From 2005 to 2030,” J. Bone Joint Surg. Am. 89:780-5 (2007)). Moreover, during the past decade the average age of patients undergoing TKR decreased from 66 to 57 years of age, a troubling trend considering the surgical difficulty and cost associated with revision arthroplasty. With the anticipated increase in disease prevalence and its associated drain on health care resources, there is a clear and pressing need to develop improved decision models with respect to the treatment of knee OA including the appropriate timing of TKR and evidence-based guidelines to indicate when the utilization of treatment alternatives is indicated.
Osteoarthritis is a complex, multifactorial disease of uncertain etiology. Current hypotheses focus on a combination of endogenous factors such as age, sex, and genetics with important contributions from exogenous factors such as repetitive weightbearing loads and traumatic events (Lohmander and Felson, “Can We Identify a ‘High Risk’ Patient Profile to Determine Who Will Experience Rapid Progression of Osteoarthritis,” Osteoarthritis Cartilage 12 Suppl. A:S49-52 (2004)). Both clinical and basic science research is presently focused not only on identifying the factors that initiate OA, but also those that contribute to its progression. While the natural history of knee OA is not clearly understood, there is data to suggest that the rate of progression of the disease is variable. This phenomenon may reflect a differential local production of inflammatory cytokines by patients based on their genetic background and the sensitivity of their innate immune system. The ability to categorize patients with symptomatic OA according to their predicted rate of disease progression would have a significant impact on decision making with respect to the recommended course of treatment, including the appropriate timing of TKR.
Biomarkers are defined as objective indicators of normal biologic processes, pathologic processes, or pharmacologic responses to therapeutic interventions (Bauer et al., “Classification of Osteoarthritis Biomarkers: A Proposed Approach,” Osteoarthritis Cartilage 14(8):723-7 (2006); De Gruttola et al., “Considerations In the Evaluation of Surrogate Endpoints In Clinical Trials. Summary of a National Institutes of Health Workshop,” Control Clin. Trials 22(5):485-502 (2001)). During the last 10 years, significant progress has been made toward developing biomarkers for osteoarthritis. For example, Sharif et al., “Suggestion of Nonlinear or Phasic Progression of Knee Osteoarthritis Based On Measurements of Serum Cartilage Oligomeric Matrix Protein Levels Over Five Years,” Arthritis Rheum. 50(8):2479-88 (2004), recently demonstrated that mean serum levels of the biomarker cartilage oligmeric matrix protein (“COMP”) was related to progressive joint damage in cases of knee OA. In their study of 115 patients, the authors reported that serum COMP levels were significantly higher amongst patients with progressive disease compared to those with quiescent disease and that on average, a one unit increase in COMP level corresponded to a 15% probability of radiographic progression over a 6 month period. In a cohort of 377 patients with symptomatic knee OA, Garnero et al., “Bone Marrow Abnormalities On Magnetic Resonance Imaging are Associated With Type II Collagen Degradation In Knee Osteoarthritis: A Three-month Longitudinal Study,” Arthritis Rheum. 52(9):2822-9 (2005), reported that MRI evidence of worsening OA-related bone marrow abnormalities could be predicted based on the urinary excretion of C-terminal crosslinking telopeptide of type II collagen (“CTX-II”). In that study, patients with baseline urinary CTX-II levels in the highest tertile had a relative risk of 2.4 of worsening bone marrow abnormalities at 3 months compared with patients with levels in the lowest tertile.
For a variety of disease states the use of biomarkers has been advantageous as a part of the diagnostic workup, helping to customize therapy for distinct patient subgroups. At the present time, the preponderance of research on the use of biomarkers has been performed using blood and urine as sample sources secondary to their ready availability. While a number of recent studies have investigated changes in synovial fluid characteristics during the OA disease process (see, e.g., Gandhi et al., “The Synovial Fluid Adiponectin-leptin Ratio Predicts Pain With Knee Osteoarthritis,” Clin. Rheumatol.,Mar. 28, 2010; Gao et al., “Elevated Osteopontin Level of Synovial Fluid and Articular Cartilage Is Associated With Disease Severity In Knee Osteoarthritis Patients,” Osteoarthritis Cartilage 18(1):82-7 (2010); Hao et al., “Synovial Fluid Level of Adiponectin Correlated With Levels of Aggrecan Degradation Markers In Osteoarthritis,” Rheumatol. Int.,May 13, 2010; Neu et al., “Friction Coefficient and Superficial Zone Protein Are Increased In Patients With Advanced Osteoarthritis,” Arthritis Rheum.,May 24, 3010; Sutipornpalangkul et al., “Lipid Peroxidation, Glutathione, Vitamin E, and Antioxidant Enzymes In Synovial Fluid from Patients With Osteoarthritis,” Int. J. Rheum. Dis. 12(4):324-8 (2009)), no data is available regarding the utility of synovial fluid biomarkers to distinguish OA subgroups, particularly as these relate to treatment recommendations and the risk of progression to severe degenerative joint disease and total knee replacement.
One reason for the limited availability of synovial fluid biomarker data is the difficulty of collecting and analyzing synovial fluid from arthritic knees that do not present with an effusion, the so-called “dry joint.” Recently, closed-needle lavage procedures have been developed which enable the standardized collection of synovial fluid for quantitative biomarker analysis (FIG. 12). Closed-needle lavage is a safe, office-based procedure which in addition to enabling the acquisition of synovial fluid for analysis has been shown to provide significant symptomatic benefit for some patients with knee OA (Chang et al., “A Randomized, Controlled Trial of Arthroscopic Surgery Versus Closed-needle Joint Lavage for Patients With Osteoarthritis of the Knee,” Arthritis Rheum. 36(3):289-96 (1993); Ike et al., “Tidal Irrigation Versus Conservative Medical Management In Patients With Osteoarthritis of the Knee: A Prospective Randomized Study. Tidal Irrigation Cooperating Group,” J. Rheumatol. 19(5):772-9 (1992)). In a prospective randomized trial of closed-needle lavage compared to conservative medical management in 77 patients with knee OA, Ike et al., “Tidal Irrigation Versus Conservative Medical Management In Patients With Osteoarthritis of the Knee: A Prospective Randomized Study. Tidal Irrigation Cooperating Group,” J. Rheumatol. 19(5):772-9 (1992), demonstrated significant differences favoring lavage with respect to pain after a 50 foot walk, pain after a 4 stair climb, frequency of knee stiffness, and overall assessment of therapy effectiveness.
There is a need for highly sensitive, specific, and quantitative assays for the determination of biomarkers that represent an overall summation of local inflammatory conditions in patient specimens. While assays for some biomarkers of inflammation are available for research purposes, these measure the quantity of the specific biomarker present, and do not provide an integrated measure of the cytokine-induced inflammatory activity present in a biological specimen.
The present invention is directed to overcoming these and other limitations in the art.